Knowledge Discovery in Databases
ZZD Acad. year 2001/2002 Winter semester 5 credits
Language of instruction
- Database Systems (IDS)
Syllabus of lectures
- Introduction - motivation, fundamental concepts, data source and knowledge types.
- Data Warehouse and OLAP Technology for Data Mining.
- Data Preparation.
- Data Mining Systems - task specification, data mining query languages, system architectures.
- Concept Description: Characterization and Comparison.
- Mining Association Rules in Transaction Data.
- Mining Association Rules in Relational Databases and Warehouses.
- Classification - decision tree, Bayesian classification, using neural networks for classification.
- Other Classification Methods. Prediction.
- Cluster Analysis.
- Mining Complex Types of Data - data mining inobject, spatial, and text data.
- Mining in Multimedia Data, Time Sequences, and Mining the WWW.
- Applications and Trends in Data Mining.
Syllabus - others, projects and individual work of students